Abstract
The Thyroid Imaging Reporting and Data System (TIRADS) is based on the ranking of a set of ultrasound signs that are most common in various thyroid pathology. The characteristics of thyroid nodules, such as clarity and regularity of margins, echogenicity, echostructure, and presence of macro- and microcalcifications, composed the basic elements of the system. It permits standardization of thyroid ultrasound reports, thus reducing the subjective aspects in the interpretation of ultrasound images. TIRADS and its modifications significantly improved the detection of thyroid tumors. European researchers presented Euro-TIRADS (EU-TIRADS). The American College of Radiologists (ACR) proposed an alternative model. Its feature is that ultrasound signs have ranking in accordance with their importance for diagnosis. The American Thyroid Association (ATA) recommended five patterns of sonographic image based on a significantly smaller number of ultrasound signs and corresponding with the risk of malignancy. Consensus statement and recommendations published by Korean scientists implied the concept of the Korean thyroid image reporting and data system (K-TIRADS). The British Thyroid Association (BTA) published their version of TIRADS—BTA thyroid nodule ultrasound (U) classification. The work on improving the efficiency of stratification systems is still in progress.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Gharib H, Papini E, Garber JR, et al. American Association of Clinical Endocrinologists, American College of Endocrinology, and Associazione Medici Endocrinologi medical guidelines for clinical practice for the diagnosis and management of thyroid nodules – 2016 update. Endocr Pract. 2016;22(Suppl 1):1–60.
Haugen BR, Alexander EK, Bible KC, et al. American Thyroid Association management guidelines for adult patients with thyroid nodules and differentiated thyroid cancer: the American Thyroid Association guidelines task force on thyroid nodules and differentiated thyroid cancer. Thyroid. 2016;26(1):1–133.
Russ G, Bonnema SJ, Erdogan MF, et al. European thyroid association guidelines for ultrasound malignancy risk stratification of thyroid nodules in adults: the EU-TIRADS. Eur Thyroid J. 2017;6:225–37.
Shin JH, Baek JH, Chung J, et al. Ultrasonography diagnosis and imaging-based management of thyroid nodules: revised Korean Society of thyroid radiology consensus statement and recommendations. Korean J Radiol. 2016;17:370–95.
Tessler FN, Middleton WD, Grant EG, et al. ACR thyroid imaging, reporting and data system (TI-RADS): white paper of the ACR TI-RADS committee. J Am Coll Radiol. 2017;14:587–95.
Fernández-Sánchez J. TI-RADS classification of thyroid nodules based on a score modified according to ultrasound criteria for malignancy. Rev Argent Radiol. 2014;78(3):138–48.
American College of Radiology, BI-RADS Committee. ACR BI-RADS breast imaging and reporting data system: breast imaging atlas. 4th ed. Reston: American College of Radiology; 2003. p. 1–86.
Aleksandrov YK, Shulutko AM, Sencha AN, et al. Diagnostic tactics for thyroid nodules based on the TIRADS system. Mosc Surg J. 2015;3(43):24–6 (In Russian).
Horvath E, Silva CF, Majlis S, et al. Prospective validation of the ultrasound based TIRADS (thyroid imaging reporting and data system) classification: results in surgically resected thyroid nodules. Eur Radiol. 2017;27(6):2619–28.
Horvath E, Majlis S, Rossi R, et al. An ultrasonogram reporting system for thyroid nodules stratifying cancer risk for clinical management. J Clin Endocrinol Metab. 2009;94(5):1748–51.
Campanella P, Ianni F, Rota CA, et al. Quantification of cancer risk of each clinical and ultrasonographic suspicious feature of thyroid nodules: a systematic review and meta-analysis. Eur J Endocrinol. 2014;170:R203–11.
Ianni F, Campanella P, Rota CA, et al. A meta-analysis-derived proposal for a clinical, ultrasonographic, and cytological scoring system to evaluate thyroid nodules: the “CUT” score. Endocrine. 2015;52(2):313–21. https://doi.org/10.1007/s12020-015-0785-5.
Tugendsam C, Petz V, Buchinger W, et al. Ultrasound criteria for risk stratification of thyroid nodules in the previously iodine deficient area of Austria - a single centre, retrospective analysis. Thyroid Res. 2018;11:3.
Moon WJ, Baek JH, Jung SL, et al. Korean Society of Thyroid Radiology (KSThR); Korean Society of Radiology. Ultrasonography and the ultrasound-based management of thyroid nodules: consensus statement and recommendations. Korean J Radiol. 2011;12:1–14.
Kwak JY, Han KH, Yoon JH, et al. Thyroid imaging reporting and data system for US features of nodules: a step in establishing better stratification of cancer risk. Radiology. 2011;260:892–9.
Grani G, Lamartina L, Ascoli V, et al. Ultrasonography scoring systems can rule out malignancy in cytologically indeterminate thyroid nodules. Endocrine. 2017;57:256–61.
Sencha AN, Patrunov YN, Mogutov MS, et al. Thyroid cancer: US THI-RADS classification, ultrasound qualitative and quantitative elastography, contrast ultrasound. Collection of scientific papers “Nevsky Radiologichesky Forum-2015”. St. Petersburg: ELBI-SPb; 2015. p. 605–8 (In Russian).
Grani G, D’Alessandri M, Carbotta G, et al. Grey-scale analysis improves the ultrasonographic evaluation of thyroid nodules. Medicine. 2015;94:1129.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Timofeyeva, L.A., Sencha, E.A., Aleksandrov, Y.K., Sencha, A.N., Tukhbatullin, M.G. (2019). TIRADS Classification as a Malignancy Risk Stratification System. In: Sencha, A., Patrunov, Y. (eds) Thyroid Ultrasound. Springer, Cham. https://doi.org/10.1007/978-3-030-14451-7_7
Download citation
DOI: https://doi.org/10.1007/978-3-030-14451-7_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-14450-0
Online ISBN: 978-3-030-14451-7
eBook Packages: MedicineMedicine (R0)